“ENVIROfying” the Future Internet

THE ENVIRONMENTAL OBSERVATION WEBFOR THE CROSS-DOMAIN FI-PPP APPLICATIONS

State and trends in mobile observation applications

iEMSs 2014, June 18-th 2014, San Diego

Denis Havlik and Gerald Schimak (AIT)

Why VGI?

2014 Denis Havlik, AIT Austrian Institute of Technology GmbH. 2

Human sensors?

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Panoramio

Sports-tracker

Waze ENVIROFI ZmapujTO

PocketLAI

e-mobiliTI

User Geo-ref. photos,

Geo-ref. photos

Hazards reports, map improvements, fuel prices…

Tree occur. and additional observations; own reactions to environment

Positions of illegal dump sites

Geo-ref. photos, inclination, weather conditions

comments and explanations for travels

System Ranking Tracks; Speed, calories hearth rate (opt.)

Car velocity, Routing

Plausibility, leaf detection, ambient pressure

Land ownership

Leaf area index

Segments; means of transport

Peers Comments, tags

Comments

Confirmations

Confirmations, development over time

Confirmations?

- -

What do we expect from users?

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Motivation matters!

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Panoramio

Sports-tracker

Waze ENVIROFI ZmapujTO

PocketLAI

e-mobiliTI

User Benefit

Backup, manage and present photos;

progress and achievements; (own, pears)

Lower cost and duration of trips

Tree identification, own reactions to environment

Higher quality of life;

Track crop growth, estimate yields

Improved awareness of own habits

Motivation boost

Peer reactions (ego)

Own achievements, peer reactions

Points for achievements

tasks, personalized alerts, feedback

Municipality and peer reactions

- by project team

Goodies Photo album

Fitness diary

Scavenger hunt

Learning about environment & health

Organise own actions

- -

Main benefactor

user user user, community

community, user

community

user project

What do users gain?

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On giving, taking and (t)askingView existing knowledge•Map view•Table view•Detailed View•Areas of Interest

View existing knowledge•Map view•Table view•Detailed View•Areas of Interest

Receive information (events!)•Requests for more observations, •Warnings, e.g. “pollen warning”•Interests, e.g. “monumental tree in vicinity”

Receive information (events!)•Requests for more observations, •Warnings, e.g. “pollen warning”•Interests, e.g. “monumental tree in vicinity”

Report observations•“New” things, e.g. “here and now I see a tree”•Personal, e.g. “I have a headache”•Obs. on existing thing, e.g. “this tree currently blossoms

Report observations•“New” things, e.g. “here and now I see a tree”•Personal, e.g. “I have a headache”•Obs. on existing thing, e.g. “this tree currently blossoms

Inform

Server Backend(or proxy)

Alert!Request Action!

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Crowd(t)ask and thou shall be given?

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Mobile Users

SensorsAutomatedTasking

External Data

ManualTasking

Decision maker

Experts Algorithms

2014 Denis Havlik, AIT Austrian Institute of Technology GmbH.

Data export

Crowd(t)asking at work

Waze sucesfully combines crowdtasking, geofencing and scavenger hunt elements

• „are you at a petrol station?“ => petrol prices

• „are you in congestion“? => congestion info, accidents

• „Collect the goodies on a map“ => road condition

(It also features geo-specific alerts)

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Microlearning and VGI

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Classical: large information intake, well in-advance to use

Illustration from Flickr, by Dean+Barb

Illustration from Flickr, by Tulane Public Relations

Incompatible with the modern lifestyle!

Learning by doing: trial and error method

Illustration from: The Black Cat Diaries

OK, unless it endangers users.

Learning while doing: just in time intake of information in small portions (microlearning)

“Danger, complex diagrams ahead”Illustration from Flickr, by Matthew Rogers

Preferably disguised as a “game”.

„Learning while doing“ examples

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Objective Possible approach

How to use the application? Tooltips or popup messages on first use (implemented)

Training to recognise objects

Scavenger hunt for known and tagged objects

Learn to avoid misidentifications

control questions & feedback

A-posteriori feedback Notify user when more info on the object is available (implemented)

Classify data & assess users knowledge

Generalized re-capcha principle

Reviewing, preparing for “tests”

Generalized flashcards

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1. The authors are in no way affiliated to any of the programs used in comparison tables (except ENVIROFI)

2. The ideas presented today were developed in the scope of the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898 (ENVIROFI)

3. Our R&D currently concentrates on crowdtasking for crisis management in the DRIVER project (Grant Agreement Number n° 607798). • Micro-training and tasking according to concrete

needs, users knowledge and capacities is a must in crisis management applications.

Acknowledgements

152014 Denis Havlik, AIT Austrian Institute of Technology GmbH.

Thank you for your attentionDr. Denis Havlik

denis.havlik@ait.ac.at

The research leading to these results has received funding from the European Community's Seventh

Framework Programme (FP7/2007-2013) under Grant Agreement Number 284898

www.envirofi.eu